Synthetic aperture radar (SAR) systems can be employed to generate SAR images of a scene. Summarily, a SAR system comprises a radar transmitter and a radar receiver placed in an aircraft that passes by a scene of interest. During a pass by the scene, the radar transmitter directs radar signals towards the scene, wherein the radar signals reflect from the scene, and the radar receiver detects the reflected radar signals. A computing system is in communication with the radar receiver, and the computing system constructs a SAR image of the scene based upon the reflected radar signals detected by the radar receiver during the pass by the scene. SAR images exhibit advantages over optical images in certain respects. For instance, radar signals emitted by the radar transmitter and received by the radar receiver can pass through cloud cover. Additionally, the SAR system can generate images of a scene at night. Still further, SAR images exhibit details that do not appear in optical images. For instance, a SAR image can depict gradations of texture (e.g., coarse to fine gravel), which are typically not able to be ascertained in optical images.
Coherent change detection (CCD) images can be generated based upon complex-valued SAR images. With more specificity, a CCD image can be generated based upon a pair of finely registered SAR images of a scene corresponding to two passes by the scene, wherein the CCD image depicts alterations in the scene that have occurred between the two passes. Stated differently, a CCD image can reveal subtle rearrangements of scatterers that are present in a single resolution cell of a complex SAR image. Each element (pixel value) in a CCD image is a realization of the sample coherence magnitude function computed over a centered local window of pixels. The sample coherence magnitude, often denoted {circumflex over (γ)}, varies between 0 and 1. Pixels with low values indicate locations in a scene where complex change has occurred between two SAR passes by the scene used to generate the CCD image, and values close to unity are found in pixels corresponding to unchanged scene elements.
CCD images have been identified as being useful for showing human activity-induced change phenomena, including vehicle tracks on a gravel road, soil displacements caused by a rotary hoe, and mowing of grass. Highlighting these changes for an analyst tasked with monitoring the scene over time can assist the analyst in determining how busy the scene has been between two SAR passes, and whether any objects of interest (vehicles, sheds, crates) have been repositioned between the two SAR passes. It can be ascertained, however, that not all areas of low coherence in a CCD image correspond to locations where human-induced change has occurred. For example, a CCD image may include pixels containing SAR shadows, standing water, or vegetation, which also typically experience a loss of phase coherence between SAR passes. When a CCD image includes several regions of low phase coherence, the analysts may be visually overwhelmed, particularly for highly cluttered scenes. Therefore, while CCD images may be helpful to an analyst who is tasked with monitoring the scene, the CCD images may not be ideal due to the CCD images potentially depicting a significant amount of clutter.